U.S. patent application number 13/572862 was filed with the patent office on 2013-05-09 for system for automatic medical ablation control.
This patent application is currently assigned to Siemens Medical Solutions USA, Inc.. The applicant listed for this patent is Hongxuan Zhang. Invention is credited to Hongxuan Zhang.
Application Number | 20130116681 13/572862 |
Document ID | / |
Family ID | 48224201 |
Filed Date | 2013-05-09 |
United States Patent
Application |
20130116681 |
Kind Code |
A1 |
Zhang; Hongxuan |
May 9, 2013 |
System for Automatic Medical Ablation Control
Abstract
A system provides heart ablation unit control. The system
includes an input processor for acquiring electrophysiological
signal data from multiple tissue locations of a heart and data
indicating tissue thickness at the multiple tissue locations. A
signal processor processes the acquired electrophysiological signal
data to identify location of particular tissue sites of the
multiple tissue locations exhibiting electrical abnormality in the
acquired electrophysiological signal data and determines an area of
abnormal tissue associated with individual sites of the particular
sites. An ablation controller automatically determines ablation
pulse characteristics for use in ablating cardiac tissue at an
individual site of the particular tissue sites in response to the
acquired data indicating the thickness of tissue and determined
area of abnormality of the individual site.
Inventors: |
Zhang; Hongxuan; (Palatine,
IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Zhang; Hongxuan |
Palatine |
IL |
US |
|
|
Assignee: |
Siemens Medical Solutions USA,
Inc.
Malvern
PA
|
Family ID: |
48224201 |
Appl. No.: |
13/572862 |
Filed: |
August 13, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61557500 |
Nov 9, 2011 |
|
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|
Current U.S.
Class: |
606/34 |
Current CPC
Class: |
A61B 2018/0075 20130101;
A61B 5/0456 20130101; A61B 5/4836 20130101; A61B 5/046 20130101;
A61B 2034/254 20160201; A61B 5/042 20130101; A61B 18/1206 20130101;
A61B 18/1492 20130101; A61B 2090/061 20160201; A61B 2018/00839
20130101; A61B 34/10 20160201; A61B 34/25 20160201; A61B 2018/00702
20130101; A61B 2018/00761 20130101; A61B 2034/256 20160201 |
Class at
Publication: |
606/34 |
International
Class: |
A61B 18/12 20060101
A61B018/12 |
Claims
1. A system for heart ablation unit control, comprising: an input
processor for acquiring electrophysiological signal data from a
plurality of tissue locations of a heart and data indicating tissue
thickness at said plurality of tissue locations; a signal processor
for processing the acquired electrophysiological signal data to,
identify location of particular tissue sites of said plurality of
tissue locations exhibiting electrical abnormality in said acquired
electrophysiological signal data and determining an area of
abnormal tissue associated with individual sites of said particular
sites; and an ablation controller for automatically determining
ablation pulse characteristics for use in ablating cardiac tissue
at an individual site of said particular tissue sites in response
to the acquired data indicating the thickness of tissue and
determined area of abnormality of the individual site.
2. A system according to claim 1, including a display processor for
generating data representing a display image showing a
representation of said plurality of tissue locations and indicating
said particular tissue sites and area of abnormal tissue associated
with said individual sites of said particular sites.
3. A system according to claim 2, wherein said representation of
said plurality of tissue locations comprises a two dimensional (2D)
or three dimensional (3D) representation of a patient heart.
4. A system according to claim 1, wherein said input processor
acquires data indicating a measured dominant rotor frequency at
said individual site and said ablation controller determines an
ablation pulse characteristic comprising pulse frequency in
response to the rotor frequency.
5. A system according to claim 1, wherein said input processor
acquires data indicating a measured dominant rotor frequency at
said individual site and said ablation controller determines an
ablation pulse characteristic comprising an ablation pulse
frequency in response to the rotor frequency by selection of said
pulse frequency from predetermined information associating ablation
pulse frequency with rotor frequency for a patient having similar
patient demographic characteristics as said patient.
6. A system according to claim 5, wherein said demographic
characteristics comprise at least one of, age, weight, gender, body
mass index and height.
7. A system according to claim 1, wherein said ablation controller
determines an ablation pulse characteristic comprising pulse width
in response to at least one, (a) said thickness of tissue and (b)
said determined area of abnormality by selection of said pulse
width from predetermined information associating ablation pulse
width with thickness of tissue and area of tissue for a patient
having similar patient demographic characteristics as said
patient.
8. A system according to claim 7, wherein said ablation controller
determines an ablation pulse characteristic comprising pulse
electrical energy in response to at least one, (a) said thickness
of tissue and (b) said determined area of abnormality by selection
of said pulse electrical energy from predetermined information
associating ablation pulse electrical energy with tissue thickness
and abnormality area for a patient having similar patient
demographic characteristics as said patient.
9. A system according to claim 1, including a severity processor
for processing the acquired electrophysiological signal data to
determine a degree of severity of abnormality at each of said
particular tissue sites and prioritizing order in which said
particular tissue sites are ablated in response to the determined
degree of severity.
10. A system according to claim 9, wherein said severity processor
processes the acquired electrophysiological signal data to
determine said degree of severity of abnormality by determining a
measure of distortion in a P wave in said electrophysiological
signal data in response to at least one of, (a) change in peak
amplitude of said P wave, (b) change in dominant frequency of said
P wave, (c) change in energy of said P wave and (d) change in time
duration between successive peaks of said P wave.
11. A system according to claim 9, including a display processor
for generating data representing a display image showing a
representation of said plurality of tissue locations and indicating
said particular tissue sites and area of abnormal tissue associated
with said individual sites of said particular sites and the
priority of order of ablation of said particular tissue sites.
12. A system according to claim 11, wherein said display processor
automatically updates said display image to show an updated area of
abnormal tissue associated with said individual sites in response
to performing ablation at said individual site.
13. A system according to claim 11, wherein said ablation
controller automatically re-determines and updates said ablation
pulse characteristics in response to performing ablation at said
individual site.
14. A system according to claim 1, including a display processor
for generating data representing a display image showing a
representation of said plurality of tissue locations and indicating
said particular tissue sites and area of abnormal tissue associated
with said individual sites of said particular sites and the
priority of order of ablation of said particular tissue sites and
said display processor updates said display image to show an
updated area of abnormal tissue associated with said individual
sites in response to performing ablation at said individual
site.
15. A system according to claim 1, wherein said ablation controller
determines an ablation pulse characteristic comprising pulse type
by selecting pulse type from, (a) a uniphase type and (a) biphase
type in response to a determined rotor signal type.
16. A system according to claim 1, wherein said ablation controller
determines ablation characteristics comprising interval between
ablation episodes and ablation duration in response to at least
one, (a) said thickness of tissue and (b) said determined area of
abnormality by selection of said pulse width from predetermined
information associating ablation pulse width with thickness of
tissue and area of tissue for a patient having similar patient
demographic characteristics as said patient.
17. A system according to claim 1, wherein said ablation controller
synchronizes ablation pulse delivery with a heart cycle
synchronization signal.
18. A system according to claim 1, wherein said ablation controller
compares areas of abnormality after ablation of said individual
site with areas of abnormality prior to ablation of said individual
site and indicates differences.
19. A method for heart ablation unit control, comprising the
activities of: acquiring electrophysiological signal data from a
plurality of tissue locations of a heart and data indicating tissue
thickness at said plurality of tissue locations; processing the
acquired electrophysiological signal data to, identify location of
particular tissue sites of said plurality of tissue locations
exhibiting electrical abnormality in said acquired
electrophysiological signal data and determining an area of
abnormal tissue associated with individual sites of said particular
sites; and automatically determining ablation pulse characteristics
for use in ablating cardiac tissue at an individual site of said
particular tissue sites in response to the acquired data indicating
the thickness of tissue and determined area of abnormality of the
individual site.
20. A method according to claim 19, including the activity of
generating data representing a display image showing a
representation of said plurality of tissue locations and indicating
said particular tissue sites and area of abnormal tissue associated
with said individual sites of said particular sites.
21. A method according to claim 20, wherein said representation of
said plurality of tissue locations comprises a two dimensional (2D)
or three dimensional (3D) representation of a patient heart.
22. A method according to claim 19, including the activity of
acquiring data indicating a measured dominant rotor frequency at
said individual site and said ablation controller determines an
ablation pulse characteristic comprising pulse frequency in
response to the rotor frequency.
23. A method according to claim 19, including the activity of
processing the acquired electrophysiological signal data to
determine a degree of severity of abnormality at each of said
particular tissue sites and prioritizing order in which said
particular tissue sites are ablated in response to the determined
degree of severity.
Description
[0001] This is a non-provisional application of provisional
application Ser. No. 61/557,500 filed Nov. 9, 2011, by H.
Zhang.
FIELD OF THE INVENTION
[0002] This invention concerns a system for heart ablation unit
control by automatically determining ablation pulse characteristics
for use in ablating cardiac tissue at an individual tissue site in
response to acquired data indicating the thickness of tissue and
determined area of abnormality of the individual site.
BACKGROUND OF THE INVENTION
[0003] Atrial fibrillation (AF) is one of most common cardiac
rhythm disorders and irregularities of cardiac patients. Usually,
surface ECG signal analysis based on waveform morphology and time
domain parameters is utilized for cardiac arrhythmia detection by P
wave signal characterization, for example. Known invasive catheter
based ablation is used for treating and terminating atrial
functional arrhythmias and electrophysiological disorders,
especially atrial fibrillation and flutters. However, known
clinical ablation and treatment procedures are based on physician
subjective estimation and require extensive clinical knowledge and
electrophysiological experience. There is a lack of an efficient
and effective ablation control system for ablation parameter
setting and adjustment, such as for control of duration of ablation
shock signals, ablation energy, ablation pulse pattern and ablation
site priority. There is also a lack of a system providing
qualitative and quantitative characterization of atrial
fibrillation, especially for quantification of severity of AF.
[0004] Usually, surface ECG signal analysis based on waveform
morphology and time domain parameters is utilized for cardiac AF
rhythm detection and characterization. Such waveform morphology
includes P wave morphology changes, R-R wave time interval, and
heart rate variability. However, known waveform morphology and time
domain parameter analysis is often subjective and time-consuming,
and requires extensive expertise and clinical experience for
accurate pathology interpretation and proper cardiac rhythm
management. Some known recent research has applied mathematical
theories to biomedical signal interpretation, such as, frequency
analysis (such as dominant frequency analysis), wavelet
decomposition analysis, statistical analysis (such as
autocorrelation analysis, coherence analysis), and nonlinear
entropy evaluation. Nevertheless, this research is focused on
generating a pathology index for qualitative cardiac AF rhythm
identification. Know methods for atrial pathology and malfunction
diagnosis and interpretation typically focus on qualitative
electrical pulse conduction and excitation progression in an atrial
chamber and tissue. There is a lack of a system able to identify
atrial arrhythmia area size and severity for ablation treatment
quantitatively, such as for an atrial fibrillation site in the
right and left atrial chambers.
[0005] Known systems track and navigate atrial chamber size,
myocardial wall thickness, tissue electrical impedance and atrial
contraction mode but fail to comprehensively determine atrial
arrhythmia treatment including ablation energy and pulse pattern
selection. Known ablation machines and electrical treatment medical
devices utilize continuous ablation shock signals for burning and
terminating abnormal tissue function, such as pathological atrial
fibrillation rotors in atrial chamber tissue but fail to
comprehensively modulate ablation energy pulses by adaptively
adjusting ablation parameters during electrical treatment including
electrical pulse length, energy and ablation time length. A system
according to invention principles addresses these deficiencies and
associated problems.
SUMMARY OF THE INVENTION
[0006] A system detects and characterizes atrial signals (including
surface ECG signals, intra-cardiac electrograms, invasive or
non-invasive atrial hemodynamic signals) to provide an accurate
event time, atrial arrhythmia type, abnormal excitation rotor
location and severity in the treatment of atrial fibrillation
arrhythmia. A system provides heart ablation unit control. The
system includes an input processor for acquiring
electrophysiological signal data from multiple tissue locations of
a heart and data indicating tissue thickness at the multiple tissue
locations. A signal processor processes the acquired
electrophysiological signal data to identify location of particular
tissue sites of the multiple tissue locations exhibiting electrical
abnormality in the acquired electrophysiological signal data and
determines an area of abnormal tissue associated with individual
sites of the particular sites. An ablation controller automatically
determines ablation pulse characteristics for use in ablating
cardiac tissue at an individual site of the particular tissue sites
in response to the acquired data indicating the thickness of tissue
and determined area of abnormality of the individual site.
BRIEF DESCRIPTION OF THE DRAWING
[0007] FIG. 1 shows a system for heart ablation unit control,
according to invention principles.
[0008] FIGS. 2A and 2B show a Table identifying ablation control
parameters and indicating their functions, according to invention
principles.
[0009] FIG. 3 illustrates comparison of a known ablation system
with an ablation system according to invention principles.
[0010] FIG. 4 shows a system for patient signal monitoring and
ablation treatment using the derived parameters of the Table of
FIG. 2, according to invention principles.
[0011] FIG. 5 shows a cardiac ablation device controller using an
artificial neural network (ANN), according to invention
principles.
[0012] FIG. 6 shows a flowchart of a method for adaptive cardiac
ablation control, according to invention principles.
[0013] FIGS. 7a and 7b show a multi-functional ablation
registration map and an associated ablation pulse sequence,
according to invention principles.
[0014] FIGS. 8, 9 and 10 present lookup tables showing tissue
abnormality and rotor characteristics and associated ablation
control parameters, according to invention principles.
[0015] FIG. 11 shows a flowchart of a process used by a system for
heart ablation unit control, according to invention principles.
DETAILED DESCRIPTION OF THE INVENTION
[0016] A system improves analysis and interpretation of cardiac
atrial electrophysiological activities for atrial pathology
diagnosis and treatment, by detecting and characterizing atrial
signals (including surface ECG signals, intra-cardiac electrograms,
invasive or non-invasive atrial hemodynamic signals) in response to
an atrial gating signal derived from a P wave signal or atrial
function portion. The gating or synchronization signal is derived
by electrical or feedback-loop control based on cardiac
measurements and derived parameters from ECG signals, hemodynamic
pressure signals, SPO2 signals including P wave start time, P wave
peak time, dP/dt (rate of pressure change), frequency and energy
waveform peak time. The system is utilized to identify, quantify
and map signal waveform changes and distortions within atrial
function signals with registration of anatomical cardiac tissue and
characterizes atrial multi-rotor (multi-excitation) signal patterns
and determines ablation treatment parameters. The system provides
an accurate event time, atrial arrhythmia type, abnormal excitation
rotor location and severity, atrial ablation mode, such as
appropriate shock energy and ablation sequence/priority in the
treatment of the atrial fibrillation arrhythmia.
[0017] Known ablation methods for atrial fibrillation typically
apply electrical shock energy and deliver electrical signals to
cardiac tissue without gating electrical ablation signals and lack
synchronization control. Known systems fail to provide adaptive
electrical shock treatment and location mapping including
adaptively varying ablation energy, ablation sequence and ablation
priority. Known systems also fail to provide automatic ablation
catheter steering in an automatic or robot based EP and Ablation
catheter control system. Know cardiac image methods in an operating
room (OR) focus on catheter insertion, stent installation and blood
flow monitoring. However a cardiac chamber and vessel are not rigid
tissue, but soft tissue, which has a contraction and reperfusion
mode and known systems typically fail to use this information for
diagnosis of cardiac soft tissue characteristics. The inventor has
identified a need for a gating system for catheter movement based
ablation control and for AF ablation with reduced noise
sensitivity.
[0018] The system employs a signal gating and synchronization
method for atrial function mapping for AF analysis and ablation
estimation that is also applicable to other portions of a cardiac
electrophysiological signal. The system is used to monitor and
diagnose pathologies and malfunctions of a heart and circulation
system during cardiac arrhythmias using cardiac arrhythmia mapping,
severity evaluation and discrimination of different cardiac
pathological rhythms including atrial tachycardia and ventricle
arrhythmias, for example.
[0019] The system provides intelligent automatically adaptive
ablation control of ablation energy, non-continuous ablation pulse
sequences, tissue location mapping and registration. The system
quantitatively and qualitatively characterizes patient cardiac
(tissue and rhythm) atrial arrhythmias using advantageous
parameters and control methods and provides atrial fibrillation
anatomical navigation, function synchronization, tissue ablation
location mapping and registration. The system provides treatment of
atrial abnormality based on atrial signal function gating and
mapping, identifies atrial tissue and rhythm disorders,
differentiates between cardiac arrhythmias, characterizes
pathological severity, predicts life-threatening events, and
supports evaluation of administered medications. The system may be
utilized in other cardiac arrhythmia detection and
characterization, such as of myocardial ischemia, ventricular
tachycardia, and ventricular fibrillation.
[0020] There are different known ablation devices including
electrical and optical devices for which a user determines specific
parameters for ablation control, such as ablation energy and
ablation duration. These parameters require a user to have
extensive electrophysiological knowledge and clinical experience.
Some ICD (implantable cardiac device) systems can perform specific
ablation and electrical shock based on specific calculations but
are susceptible to false alarms causing unnecessary false ablation
and a substantial safety risk. In contrast, the system
advantageously provides a closed loop system with substantially
optimum parameters to avoid over burning and unwanted ablation by
using atrial information and adaptive ablation control using
non-continuous ablation with adjustable ablation pulse
characteristics and duration, for example. Advantageous ablation
control parameters are generated and used for ablation pattern
control, which increases usability, reliability and efficiency of
an ablation device.
[0021] Known systems typically display ablation application related
parameters including, temperature (for monitoring an ablation tip),
tissue impedance (for monitoring ablation effectiveness), ablation
energy (for controlling delivered energy to cardiac tissue) and
time duration (for controlling maximum ablation time duration for
each ablation procedure). In contrast, the system provides ablation
severity and priority based on registration of cardiac anatomical
navigation data and intra-cardiac signal function location.
[0022] FIG. 1 shows system 10 for heart ablation unit control using
closed loop automatic ablation selection and determination for real
time adaptive ablation parameter control. Input processor 12
continuously acquires patient signals (including ablation related
intra-cardiac electrograms, surface ECG, NIBP/IBP, vital signs)
from a patient and heart 46. Processor 12 acquires
electrophysiological signal data from multiple tissue locations of
a heart and data indicating tissue thickness at the tissue
locations The invasive and ICEG data and signals are associated
(mapped) to corresponding tissue locations indicated in a
predetermined anatomical 2D or 3D image 43. The signal information
and predetermined ablation points, are dynamically mapped into a
registered ablation image 43. Ablation image 43 identifies tissue
locations that are associated with calculated parameters to provide
a visualization of function, anatomy and treatment concurrently to
facilitate adaptive automatic ablation system control and ablation
procedure optimization. The parameters include sequence of
ablation, ablation time, energy for each ablation point,
minimization of treatment time, optimum method for ablation
catheter steering, severity of cardiac condition Specifically,
image location 51 is associated with impedance, rotor cycle,
severity of condition, ablation energy level and priority (order)
in which it is to be ablated. Atrial tissue parameters including
impedance, temperature and IECG function data are also recorded,
updated and quantitatively characterized with severity and ablation
sequence (the shade, color or other visual attribute in image 43
indicates high severity, abnormality, location, and ablation energy
level).
[0023] Processing device 30 (e.g. a computer, controller, server)
includes signal processor 15, display processor 27, severity
processor 23 and repository 17. Signal processor 15 processes the
acquired electrophysiological signal data to identify location of
particular tissue sites of the multiple tissue locations exhibiting
electrical abnormality in the acquired electrophysiological signal
data and determines an area of abnormal tissue associated with
individual sites of the particular sites. Processor 15 provides a
visual location image map 45 in 2D or 3D (two or three dimensions)
registered with cardiac locations known by ablation controller 18
and locatable by controller 18 in automatically steering an
ablation catheter for ablation, for example. Image 45 identifies
tissue locations to be ablated, the ablation parameters to be used
for each location as well as the condition and severity of
condition at each location. Ablation controller 18 uses the data
associated with image 45 in automatically determining ablation
pulse characteristics for use in ablating cardiac tissue at an
individual site of the particular tissue sites in response to the
acquired data indicating the thickness of tissue and determined
area of abnormality of the individual site.
[0024] FIGS. 2A and 2B show a Table including column 203
identifying advantageous ablation control parameters 210, 212, 214,
216, 218, 220, 222 and 224 determined and used by signal processor
15. Column 206 indicates the functions of these parameters and
their applications. The ablation control parameters comprise,
ablation starting time (trigger and synchronizing/gating timing) T1
210, ablation frequency 212, tissue wall thickness 214, ablation
effective area (dependent on catheter to tissue pressure) 216,
registration and mapping of EP functions to ablation points 218,
sequence and priority of tissue locations for ablation 220,
ablation duration 222 and non-continuous ablation dynamic pulse
pattern (using unipolar or bipolar pulses) 224. The parameters are
used for ablation synchronization timing T1, for ablation energy
application to atrial tissue, dynamic dominant ablation frequency
selection for each ablation, tissue wall thickness selection,
catheter to tissue impedance and touching force selection and
selection of ablation pulse type (which is to be delivered to
cardiac tissue). In another embodiment, other parameters (such as
produced from ECG signals, hemodynamic signals, vital signs
signals, and derived signals) are used to control an ablation
procedure, ablation workflow and ablation efficiency.
[0025] FIG. 3 illustrates comparison of a known ablation procedure
shown in map 303 with a system 10 procedure shown in map 306 using
advantageous parameters, an ablation site priority and ablation
site sequence. Shade or color (or other visual attribute) of map
elements indicate severity of tissue corresponding to an element.
In a known method, ablation is performed of abnormal
electrophysiological (EP) sites based on EP signal acquisition and
ablation convenience to eliminate one area completely and to start
a next area. This may not be efficient since a multiple site
abnormality may be linked electrophysiologically and functionally
which means one area may not be able to be terminated completely
presenting risk of over burning normal tissue and introducing an
abnormality. System 10 (FIG. 1) advantageously in one embodiment
analyzes the electrophysiological characteristics of multiple sites
and creates an ablation priority and sequence. The ablation
sequence may be an ablation site combination associated with EP
signal abnormality and electrophysiological conduction and
excitation propagation. In the example in FIG. 3, 11 sites are
ablated in the known ablation method of map 303 in 30 minutes using
200 Watts of energy and 5 sites are ablated in the advantageous
ablation method of map 306 in 10 minutes using 50 Watts of energy.
In this way, the ablation completion time is reduced by 20 minutes.
In map 303, there are 3 ablation sites comprising normal function
tissue which do not need to be ablated. The system determines an
ablation sequence and priority that is dynamically updated
continuously and in real time.
[0026] FIG. 4 shows system 400 for patient signal monitoring and
ablation treatment using the derived parameters of the Table of
FIG. 2 employing a closed loop feedback ablation and catheter
steering system and dynamic continuous ablation signal adjustment.
System 400 advantageously synchronizes and sequences ablation of
sites and dynamically and adaptively selects ablation pulse
parameters and a pulse pattern. The parameters may be derived using
different patient signals and calculated data. Ablation pulse
parameters and a pulse pattern are dynamically updated in response
to command signals sent to an ablation controller unit. Input
processor 412 continuously acquires patient signals (including
ablation related intra-cardiac electrograms, surface ECG, NIBP/IBP,
vital signs) from a patient and heart 446. Processor 412 acquires
electrophysiological signal data from multiple tissue locations of
a heart and data indicating tissue thickness at the tissue
locations. The invasive and ICEG data and signals are associated
(mapped) to corresponding tissue locations indicated in a
predetermined anatomical 2D or 3D image 443.
[0027] Processing device 430 (e.g. a computer, controller, server)
processes the acquired electrophysiological signal data, X-ray
system information, or ultrasound information and blood flow
information, to identify location of particular tissue sites of the
multiple tissue locations exhibiting electrical abnormality in the
acquired electrophysiological signal data and determines an area of
abnormal tissue associated with individual sites of the particular
sites. Device 430 acquires data including an anatomical image of
cardiac tissue and chambers comprising an X-ray image, blood flow
image or ultrasound image, for example. The composite image and
function data derived using patient electrophysiological and
hemodynamic signals are used by the computer to determine ablation
sequence, ablation priority, ablation energy, ablation duration.
For example, by using surface ECG or ICEG signals, the computer
determines an ablation pulse start time and duration for each
ablation. The ablation pulse width is determined and adjusted based
on the real time patient signals and function changes.
[0028] Device 430 provides a visual location image map 445 in 2D or
3D (two or three dimensions) registered with cardiac locations
known by ablation controller 418 and locatable by controller 418 in
automatically steering an ablation catheter for ablation, for
example. Device 430 generates an ablation trigger, gating and
synchronization signal 463 to start ablation and selects an
ablation pulse pattern and pulse characteristics 465. Image 445
identifies tissue locations to be ablated, the ablation parameters
to be used for each location as well as the condition and severity
of condition at each location. Ablation controller 418 uses the
data associated with image 445, synchronization signal 463 and
pulse characteristics 465 in ablating cardiac tissue at an
individual site of the particular tissue sites in response to the
acquired data indicating the thickness of tissue and determined
area of abnormality of the individual site.
[0029] Device 430 determines real time mapping and registration,
optimum appropriate ablation time, ablation pulse width and rate,
ablation delivery location and ablation energy. In addition, the
ablation duration, frequency range (band and dominant frequency)
and catheter movement information (moving to an optimum ablation
location and movement speed) for each ablation point are provided
to a physician and used in control of the ablation procedure.
Multiple methods may be used to provide image 445 and data
representation, such as by using a fuzzy system or expert system,
for example.
[0030] FIG. 5 shows a cardiac ablation device controller and multi
ablation parameter based decision system using an artificial neural
network (ANN) 507. The ANN calculation and decision module 507 has
self-learning ability involving processing training data. The ANN
based control of ablation signals uses patient signal analysis
results, patient history and physician experience (input and
suggested control mode) to provide quantitative and qualitative
control and adjustment of an ablation device. ANN unit 507 derives
detailed ablation parameters for ablation control of ablation
synchronization, ablation pulse width, ablation priority and
severity and ablation site location.
[0031] ANN unit 507 combines and maps input parameters 520, 523 and
526, to parameters processed by calculation unit 528 that provides
output parameters 529. The output parameters 529 indicate ablation
site position, type, severity and relative priority for treatment,
ablation energy, ablation duration, timing and dominant frequency,
ablation pulse type and pattern, ablation efficiency and risk and
synchronization. ANN unit 507 structure comprises 3 layers, an
input layer 510, hidden layer 512 and output layer 514. ANN unit
A.sub.ij weights are applied between input layer 510 and hidden
layer 512 components of the ANN computation and B.sub.pq weights
are applied between hidden layer 512 and calculation components 514
of the ANN computation. The A.sub.ij weights and B.sup.pq weights
are adaptively adjusted and tuned using a training data set.
[0032] FIG. 6 shows a flowchart of a method for adaptive cardiac
ablation control used by system 10 (FIG. 1). Input processor 12
buffers, filters (to remove power line noise, patient movement and
respiration noise) and digitizes an ECG signal, ICEG signal,
invasive and non-invasive blood pressure signals, respiration
signals, SPO2 signals and vital signs signals in step 608 received
from a patient in step 606. Processor 15 in step 608 filters the
received signal data using a filter adaptively selected in response
to data indicating clinical application, to remove patient movement
and respiratory artifacts as well as power line noise. In step 612,
processor 15 detects patient signal parameters and segments an ECG
signal into sections including, P wave, Q wave, R wave, S wave, T
wave, U wave portions and determines peak timing and
end-of-diastolic (EoD) and end-of-systolic (EoS) points.
[0033] The P wave, Q wave, R wave, S wave, T wave, U wave portions
and points of the received ECG signal are identified by detecting
peaks within the received ECG data using a known peak detector and
by segmenting the ECG signal into windows where the waves are
expected and by identifying the peaks within the windows. The start
point of a wave, for example, is identified by a variety of known
different methods. In one method a wave start point comprises where
the signal crosses a baseline of the signal (in a predetermined
wave window, for example). Alternatively, a wave start point may
comprise a peak or valley of signal. The baseline of the signal may
comprise a zero voltage line if a static (DC) voltage signal
component is filtered out from the signal. The signal processor
includes a timing detector for determining time duration between
the signal peaks and valleys. The time detector uses a clock
counter for counting a clock between the peak and valley points and
the counting is initiated and terminated in response to the
detected peak and valley characteristics.
[0034] In step 614, processor 15 performs anatomical navigation of
a catheter for image acquisition and ECG, ICEG and EP signal
acquisition and mapping to, (and association with), cardiac tissue
locations on an X-ray image, ultrasound image or other cardiac
image, for example. Signal processor 15 in step 616 performs
ablation related parameter calculation and selection including
deriving appropriate ablation control signals, an ablation site
sequence, selection of ablation pulse type and pattern, a dynamic
ablation frequency range and real time feedback controlled ablation
energy using a lookup table as in FIG. 2. Processor 15 in step 620
generates ablation control signals for adaptive ablation and
treatment of a patient.
[0035] If signal processor 15 in step 626, determines a new
ablation process is to be performed using an updated ablation
mapping of tissue sites to be ablated, the process is repeated from
step 608. If a new ablation process is not to be performed,
processor 15 in step 635 performs adaptive ablation and treatment
of a patient, using the generated parameters and control signals
and closed loop ablation system control. The system employs dynamic
real time ablation registration of sites with an image map and
adaptive update of ablation site sequence, priority, location and
applied energy. In step 637 processor 15 stores data representing
the ablation parameters used for ablation in repository 17.
Processor 15 in step 623 adaptively adjusts ablation parameters and
a control method in response to user input and tissue site severity
and current ablation treatment and control parameters.
[0036] FIGS. 7a and 7b show a multi-functional ablation
registration map and an associated ablation pulse sequence
illustrating ablation mapping and anatomical and ICEG signal
function registration. The ablation registration map 703 shows
ablation priority and sequence for left atrial chamber 705 with
ablation triggered in response to a surface ECG or an IECG signal.
Processor 15 provides a treatment suggestion and analysis 707 based
on the mapping 703. The ablation pulse duration for each ablation
is controlled and gated by the surface ECG or IECG signal.
Multi-functional ablation registration map 703 shows three
significant abnormal rotor areas in a left atrial chamber. In order
to achieve the best ablation result (ablation time and low energy
burning), a P wave 712 (derived from Surface ECG signal 710) pulse
is used as a gating window for ablation signal duration control for
each ablation site 714.
[0037] System 10 (FIG. 1) generates ablation control signals in
response to advantageous parameters including ablation sequence,
ablation gating, ablation time duration, ablation dominant
frequency and ablation pulse pattern and processor 15 superimposes
the parameter data on associated locations on an anatomical image.
The data superimposed includes ICEG signal function data
(amplitude, dominant frequency component, energy, complexity).
There are 3 abnormal atrial fibrillation rotors in the ablation
mapping. Processor 15 determines from site ICEG signals an ablation
sequence for the ablation procedure comprising, site 1, then site 2
and then site 3. The ablation sequence is an adaptive procedure and
after each ablation, the site registration mapping is updated to
guide a user for optimized ablation. Ablation for each site is
non-continuous ablation and an ablation process is segmented into
portions and is synchronized by signal 712 so time duration of each
ablation occurs within one heart cycle. The ablation time for each
site depends on the severity and abnormality of the AF rotors. For
example, in this case, site 1 needs ablation twice while site 2
needs once and site 3 need 3 times (where 1 time=pulse duration t,
2 times=2t and so on). The ablation for each site depends on local
cardiac tissue properties (such as tissue wall thickness,
electrophysiological characteristics). In this example, the
ablation time durations for the sites are: 0.5, 0.4, 0.8 seconds
respectively. In order to achieve the best ablation results, the
ablation signal mode and dominant frequency may need to be varied.
In this example, for site 1, a uniphasic ablation pulse with
dominant frequency around 474 K Hz is used. Site 2 and site 3 use
uniphasic and biphasic separation with dominant frequency focusing
on 450K Hz and 500 K Hz.
[0038] The system determines priority of ablation of tissue site
based on severity of abnormality of the tissue sites (the higher
the severity the higher the priority and order in which the site is
ablated). The severity is determined from distortion of a Pwave of
the electrophysiological signal at the site (e.g. acquired using a
basket catheter). The distortion is derived based on measurement of
P wave peak amplitude, peak amplitude variation, peak timing
latency i.e. timing shift and dominant frequency change. Patient
ablation and treatment varies based on patient gender, age,
demographic data, health status, prior cardiac treatment (e.g.
surgery) and medication. For the example in FIG. 7, cardiac patient
parameters and characteristics employed to determine ablation
treatment include ablation time, ablation duration, ablation
frequency, ablation energy and ablation pulse type. Other
parameters may be used for ablation parameter determination and
dynamic adjustment of treatment and surgery, such as tissue wall
thickness, P wave amplitude, P wave total energy, frequency ratio,
P wave time-frequency distribution and clinical procedure type.
[0039] FIGS. 8, 9 and 10 present lookup tables showing tissue
abnormality and rotor characteristics and associated ablation
control parameters. Table 803 (FIG. 8) associates a size range of
an abnormal tissue area showing Atrial Fibrillation (column 805)
with a tissue thickness range (column 807), number of ablation
pulses of a fixed width that are separated or combined into an
extended pulse width (column 809) and with an ablation time
duration (column 811). The larger the abnormality tissue area size
and the greater the severity of the abnormality, the more ablation
pulses and energy ablation duration is applied. Table 823 (FIG. 9)
associates an Atrial Fibrillation rotor dominant frequency range
(column 825) with an ablation frequency (column 827). Processor 15
identifies a dominant frequency in a P wave acquired from an
abnormal tissue site of a patient and uses Table 823 to determine a
corresponding ablation frequency to terminate fibrillation. An
ablation frequency is adaptively selected for each patient.
[0040] Table 843 (FIG. 10) shows AF rotor entry characteristics
used by processor 15 for determining an ablation pulse to be used
for each identified abnormal area. Table 843 associates Atrial
Fibrillation rotor characteristics, e.g., type of rotor such as
single phase, biphase (column 845) with type of ablation pulse
used, e.g. uniphase, biphase (column 847). If an AF rotor is
complicated in phase and shape, a multi-phasic ablation pulse
pattern is used for treatment of AF.
[0041] FIG. 11 shows a flowchart of a process used by system 10
(FIG. 1) for heart ablation unit control. In step 912 following the
start at step 911, input processor 20 acquires electrophysiological
signal data from multiple tissue locations of a heart, data
indicating tissue thickness at the multiple tissue locations and
data indicating a measured dominant rotor frequency at an
individual site. In step 915 signal processor 15 processes the
acquired electrophysiological signal data to, identify location of
particular tissue sites of the multiple tissue locations exhibiting
electrical abnormality indicated by the acquired
electrophysiological signal data and determines an area of abnormal
tissue associated with individual sites of the particular sites.
Ablation controller 18 in step 917 automatically determines
ablation pulse characteristics for use in ablating cardiac tissue
at an individual site of the particular tissue sites in response to
the acquired data indicating the thickness of tissue and determined
area of abnormality of the individual site.
[0042] Ablation controller 18 determines an ablation pulse
characteristic comprising an ablation pulse frequency in response
to the rotor frequency by selection of the pulse frequency from
predetermined information associating ablation pulse frequency with
rotor frequency for a patient having similar patient demographic
characteristics as the patient. The demographic characteristics
comprise at least one of, age, weight, gender, body mass index and
height. Ablation controller 18 determines an ablation pulse
characteristic comprising pulse width in response to at least one,
(a) the thickness of tissue and (b) the determined area of
abnormality, by selection of the pulse width from predetermined
information associating ablation pulse width with thickness of
tissue and area of tissue for a patient having similar patient
demographic characteristics as the patient. Ablation controller 18
determines an ablation pulse characteristic comprising pulse
electrical energy in response to at least one, (a) the thickness of
tissue and (b) the determined area of abnormality by selection of
the pulse electrical energy from predetermined information
associating ablation pulse electrical energy with tissue thickness
and abnormality area for a patient having similar patient
demographic characteristics as the patient. Ablation controller 18
also determines an ablation pulse characteristic comprising pulse
type by selecting pulse type from, (a) a uniphase type and (a)
biphase type in response to a determined rotor signal type. The
ablation controller automatically re-determines and updates the
ablation pulse characteristics in response to performing ablation
at the individual site and synchronizes ablation pulse delivery
with a heart cycle synchronization signal. Ablation controller 18
compares areas of abnormality after ablation of the individual site
with areas of abnormality prior to ablation of the individual site
and indicates differences and adaptively alters the selection of
ablation sites and ablation characteristics in response to the
differences.
[0043] In step 923, display processor 27 generates data
representing a display image showing a representation of the
multiple tissue locations and indicating the particular tissue
sites and area of abnormal tissue associated with the individual
sites of the particular sites. The representation of the multiple
tissue locations comprises a two dimensional (2D) or three
dimensional (3D) representation of a patient heart. Display
processor 23 automatically updates the display image to show an
updated area of abnormal tissue associated with the individual
sites in response to performing ablation at the individual site.
Severity processor 23 in step 926 processes the acquired
electrophysiological signal data to determine a degree of severity
of abnormality at each of the particular tissue sites and
prioritize order in which the particular tissue sites are ablated
in response to the determined degree of severity. Severity
processor 23 processes the acquired electrophysiological signal
data to determine the degree of severity of abnormality by
determining a measure of distortion in a P wave in the
electrophysiological signal data in response to at least one of,
(a) change in peak amplitude of the P wave, (b) change in dominant
frequency of the P wave, (c) change in energy of the P wave and (d)
change in time duration between successive peaks of the P wave. The
process of FIG. 11 terminates at step 931.
[0044] A processor as used herein is a device for executing
machine-readable instructions stored on a computer readable medium,
for performing tasks and may comprise any one or combination of,
hardware and firmware. A processor may also comprise memory storing
machine-readable instructions executable for performing tasks. A
processor acts upon information by manipulating, analyzing,
modifying, converting or transmitting information for use by an
executable procedure or an information device, and/or by routing
the information to an output device. A processor may use or
comprise the capabilities of a computer, controller or
microprocessor, for example, and is conditioned using executable
instructions to perform special purpose functions not performed by
a general purpose computer. A processor may be coupled
(electrically and/or as comprising executable components) with any
other processor enabling interaction and/or communication
there-between. Computer program instructions may be loaded onto a
computer, including without limitation a general purpose computer
or special purpose computer, or other programmable processing
apparatus to produce a machine, such that the computer program
instructions which execute on the computer or other programmable
processing apparatus create means for implementing the functions
specified in the block(s) of the flowchart(s). A user interface
processor or generator is a known element comprising electronic
circuitry or software or a combination of both for generating
display elements or portions thereof. A user interface comprises
one or more display elements enabling user interaction with a
processor or other device.
[0045] An executable application, as used herein, comprises code or
machine readable instructions for conditioning the processor to
implement predetermined functions, such as those of an operating
system, a context data acquisition system or other information
processing system, for example, in response to user command or
input. An executable procedure is a segment of code or machine
readable instruction, sub-routine, or other distinct section of
code or portion of an executable application for performing one or
more particular processes. These processes may include receiving
input data and/or parameters, performing operations on received
input data and/or performing functions in response to received
input parameters, and providing resulting output data and/or
parameters. A graphical user interface (GUI), as used herein,
comprises one or more display elements, generated by a display
processor and enabling user interaction with a processor or other
device and associated data acquisition and processing
functions.
[0046] The UI also includes an executable procedure or executable
application. The executable procedure or executable application
conditions the display processor to generate signals representing
the UI display images. These signals are supplied to a display
device which displays the elements for viewing by the user. The
executable procedure or executable application further receives
signals from user input devices, such as a keyboard, mouse, light
pen, touch screen or any other means allowing a user to provide
data to a processor. The processor, under control of an executable
procedure or executable application, manipulates the UI display
elements in response to signals received from the input devices. In
this way, the user interacts with the display elements using the
input devices, enabling user interaction with the processor or
other device. The functions and process steps herein may be
performed automatically or wholly or partially in response to user
command An activity (including a step) performed automatically is
performed in response to executable instruction or device operation
without user direct initiation of the activity.
[0047] The system and processes of FIGS. 1-11 are not exclusive.
Other systems, processes and menus may be derived in accordance
with the principles of the invention to accomplish the same
objectives. Although this invention has been described with
reference to particular embodiments, it is to be understood that
the embodiments and variations shown and described herein are for
illustration purposes only. Modifications to the current design may
be implemented by those skilled in the art, without departing from
the scope of the invention. The system detects and characterizes
atrial signals (e.g. ECG signals) in response to an atrial gating
signal derived from a P wave signal or atrial function portion and
identifies and maps signal waveform changes to anatomical cardiac
tissue in characterizing atrial multi-rotor (multi-excitation)
signal patterns for determining ablation treatment parameters.
Further, the processes and applications may, in alternative
embodiments, be located on one or more (e.g., distributed)
processing devices on a network linking the units FIG. 1. Any of
the functions and steps provided in FIGS. 1-11 may be implemented
in hardware, software or a combination of both. No claim element
herein is to be construed under the provisions of 35 U.S.C. 112,
sixth paragraph, unless the element is expressly recited using the
phrase "means for."
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